calcBias: Bias between Predicted and Actual Thermal Sensation Vote

In marcelschweiker/comfort_R: Models and Equations for Human Comfort Research

Bias between Predicted and Actual Thermal Sensation Vote

Description

calcMeanBias calculates the mean bias and its standard deviation and standard error between predicted thermal sensation votes and actual obtained sensation votes

Usage

calcBias(ref, pred)

calcbias(ref, pred)

calcMeanBias(ref, pred)

MeanBias(ref, pred)

meanBias(ref, pred)

meanbias(ref, pred)

bias(ref, pred)

calcSdBias(ref, pred)

calcSeBias(ref, pred)

Arguments

ref	a numeric item or vector containing categorical actual thermal sensation votes coded from -3 'cold' to +3 'hot'
pred	a numeric item or vector containing categorical predicted thermal sensation votes coded from -3 'cold' to +3 'hot'

Value

calcMeanBias returns a dataframe with the following items:

meanBias	single value presenting the mean bias between actual and predicted thermal sensation votes
sdBias	single value presenting the standard deviation of the mean bias
seBias	single value presenting the standard error of the mean bias

Author(s)

Marcel Schweiker. Further contribution by Shoaib Sarwar.

References

Humphreys & Nicol (2002) <doi:10.1016/S0378-7788(02)00018-X>

Schweiker & Wagner (2016) Exploring potentials and limitations of the adaptive thermal heat balance framework Proceedings of 9th Windsor Conference: Making Comfort Relevant Cumberland Lodge, Windsor, UK, 2016.

See Also

calcTPRTSV, calcAvgAcc

Examples

## Define data
ref <- rnorm(5) # actual thermal sensation votes

pred <- rnorm(5) # predicted thermal sensation votes

calcBias(ref, pred)

marcelschweiker/comfort_R documentation built on Feb. 22, 2024, 9:04 p.m.